code: def is_onnxruntime_training_available():
      """
      Checks if onnxruntime-training is available.
      """
      path_training_dependecy = os.path.join(
          ort.__path__[0], "training"
      )
      if os.path.exists(path_training_dependecy):
          return True
      else:
          return False
  
imports: import os
  import re
  from enum import Enum
  from inspect import signature
  from typing import Callable, Dict, List, Optional, Tuple, Union
  import numpy
  import torch
  from packaging import version
  from transformers.utils import logging
  import onnxruntime
  from ..exporters.onnx import OnnxConfig, OnnxConfigWithLoss
  from ..utils.import_utils import _is_package_available
label_desc: Use image node_id 2 for calling a global function with example usage: is_onnxruntime_training_available() and returns: True, False